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Public neuroscience datasets are abundant, but they prove difficult to translate into targets due to complexities with brain regions, cell types and more.
Using Alzheimer’s disease as a case study, our webinar will explore how you can combine causal relationship evidence with deeply curated neurodegenerative and neuroinflammatory disease cohorts to prioritize targets relevant to the central nervous system (CNS).
You will learn
- To identify hub genes and validate human CNS cell-type expression
> Which candidates align with CNS cell types (e.g., neurons, astrocytes, microglia, oligodendrocytes), supporting biological plausibility?
- To triage candidates based on known drug evidence
> Which candidates intersect with known drug targets or pharmacology, enabling rapid triage?
- To extend insights into related neurological indications
> How can network context and cohort evidence support indication expansion into related neurodegenerative or neuroinflammatory disorders?
By tv.qiagenbioinformatics.comPublic neuroscience datasets are abundant, but they prove difficult to translate into targets due to complexities with brain regions, cell types and more.
Using Alzheimer’s disease as a case study, our webinar will explore how you can combine causal relationship evidence with deeply curated neurodegenerative and neuroinflammatory disease cohorts to prioritize targets relevant to the central nervous system (CNS).
You will learn
- To identify hub genes and validate human CNS cell-type expression
> Which candidates align with CNS cell types (e.g., neurons, astrocytes, microglia, oligodendrocytes), supporting biological plausibility?
- To triage candidates based on known drug evidence
> Which candidates intersect with known drug targets or pharmacology, enabling rapid triage?
- To extend insights into related neurological indications
> How can network context and cohort evidence support indication expansion into related neurodegenerative or neuroinflammatory disorders?